Communication Stack Research Articles

REFLOOD: Reactive routing protocol for wake-up radio in IoT

The Internet of Things and the Wireless Sensor Networks are providing new ways to connect physical variables from the environment to the cybernetic world. As their applications become more ubiquitous, they require better energy efficiency to reduce the size of the batteries or extend their lifetime as much as possible, while keeping good quality network performance. Traditional solutions to this challenge have used a duty-cycle approach at the medium access control layer of the communication stack trading off latency for energy efficiency. Wake-up radios is a new technology for wireless communications that promises the end of this tradeoff thanks to its ultra-low power consumption. This module is attached to a regular node as a secondary receiver that listens to the channel continuously while the main radio stays sleeping. Unfortunately, the sensitivity of the wake-up receiver is very low creating a range mismatch with the main radio. This leads to very dense networks according to the very short range of the wake-up radio. In such a scenario, the data frame must pass through every node in the path from source to destination, wasting the benefits of the main radio technology. To take advantage of the full range of the main radio, the signals on the wake-up radio have to be routed through intermediate nodes before waking up the destination, so that the data can be sent directly from source to destination. In this article, we present REFLOOD, a reactive routing protocol for WuR networks that tackles this challenge taking advantage of multiple paths and achieving load balancing. We compare it with a proactive approach as well as a traditional solution in ContikiOS, through simulations in different scenarios for convergecast traffic. The results show that REFLOOD represents an improvement to 300% of the network lifetime of traditional solutions. Its multi-path feature maximizes the chances to wake-up a destination successfully, improving the packet delivery ratio, and reducing the latency.

CoAP Acceleration on FPSoC for Resource Constrained Internet of Things Devices

Data communication stack on Internet of Things (IoT)-devices is traditionally implemented in software as a part of their operating systems. In IoT-applications for which resource constrained IoT-devices are deployed, leveraging microprocessor(s) for both computing and data communication tasks may result in poor application performance and high power consumption. In order to alleviate these performance and power issues, using System on Chip (SoC) field programmable gate arrays (FPGAs) for the hardware acceleration of the performance- or power-critical software tasks is a recent, popular trend in the literature. On the other hand, constrained application protocol (CoAP) is a pivotal network protocol for many IoT-applications. Motivated by these facts, in this article, a hardware accelerator for a CoAP server network stack is proposed and realized on a SmartFusion2 SoC FPGA. The hardware accelerated CoAP server network stack is thoroughly evaluated and compared in terms of its performance, latency, power consumption, and FPGA resource utilization against a baseline software implemented CoAP server network stack. The evaluation results obtained clearly show that the CoAP hardware accelerator provides significantly higher performance and lower response message latency, while consuming significantly less power. Consequently, the CoAP hardware accelerator proposed seems to be a strong viable solution for the resource constrained IoT-devices.

XERIS/APEX

Modern day cloud native applications have become broadly representative of distributed systems in the wild. However, unlike traditional distributed system models with conceptually static designs, cloud-native systems emphasize dynamic scaling and on-line iteration (CI/CD). Cloud-native systems tend to be architected around a networked collection of distinct programs ("microservices") that can be added, removed, and updated in real-time. Typically, distinct containerized programs constitute individual microservices that then communicate among the larger distributed application through heavy-weight protocols. Common communication stacks exchange JSON or XML objects over HTTP, via TCP/TLS, and incur significant overhead, particularly when using small size message sizes. Additionally, interpreted/JIT/VM-based languages such as Javascript (NodeJS/Deno), Java, and Python are dominant in modern microservice programs. These language technologies, along with the high-overhead messaging, can impose superlinear cost increases (hardware demands) on scale-out, particularly towards hyperscale and/or with latency-sensitive workloads.

RGraph: Asynchronous graph processing based on asymmetry of remote direct memory access

SummaryThe scale of real‐world graphs is constantly growing. To deal with large‐scale graphs, distributed graph processing has attracted much research efforts. Existing distributed graph processing systems are commonly built on traditional TCP/IP communication stack, which leads to network bottleneck because of low bandwidth and heavy kernel stack operations. Meanwhile, in real power‐law graphs, the average number of mirror vertices after graph partitioning is very large, resulting in significant communication overhead among nodes. The emerging high‐performance Remote Direct Memory Access (RDMA) network has the features of low latency, high bandwidth, and low CPU overhead, which brings new opportunities for distributed graph processing systems. Existing RDMA‐assisted graph processing systems focus on synchronous execution, which imposes barriers between consecutive iterations. Synchronous execution transfers bulk data among nodes and thus only needs a small number of network transfers. However, synchronous execution is usually less efficient than asynchronous execution because of bulk synchronization. Asynchronous execution accelerates graph processing by eliminating barriers, which in turn requires to transfer a large amount of small size data. In this paper, we propose RGraph, an RDMA‐assisted asynchronous distributed graph processing system. RGraph distributes edges into two parts to isolate master and mirror vertices. RGraph exploits the asymmetry of RDMA to accelerate the one‐to‐many communication between master and mirror vertices. We implement RGraph on top of PowerGraph and conduct comprehensive experiments with large‐scale real graphs to evaluate its performance. Results show that compared to existing designs, RGraph reduces the execution time by up to 81%.

HYBRID DEEP NEURAL NETWORK ANOMALY DETECTION SYSTEM FOR SCADA NETWORKS

SCADA systems are more and more targeted by cyber-attacks because of many vulnerabilities inhardware, software, protocols and the communication stack. Those systems nowadays use standard hardware, software, operating systems and protocols. Furthermore, SCADA systems which used to be air-gaped are now interconnected to corporate networks and to the Internet, widening the attack surface.In this thesis, we are using a deep learning approach to propose an efficient hybrid deep neural network for anomaly detection in SCADA systems. The salient features of SCADA data are automatically and unsupervisingly learnt, and then fed to a supervised classifier in order to dertermine if those data are normal or abnormal, i.e if there is a cyber-attack or not. Afterwards, as a response to the challenge caused by high training time of deep learning models, we proposed a distributed approach of our anomaly detection system in order lo lessen the training time of our model.

Investigation of MAC Algorithms for Cross-Boundary Exchange between Wireless Sensor Networks

Increasing deployments of wireless sensor networks (WSNs), following the trend of the Internet of Thing (IoT), heightens the probability of the spatial overlap between WSNs in the same local area. The direct communication between distinctive networks can be supported by the direct interconnection between sensor nodes in any possible intersecting area. The packet transfer between the neighbouring networks offers multiple benefits by sharing data or network resources. However, the communication protocol adopted by each WSN can be different due to its conditions design and preferences preventing transmission and reception of packets from other network domains. One of the possible solutions for the compatibility problem is using a lightweight communication protocol for communication across the boundary while allowing networks to use its preferred communication stack inside its domain. This work investigates the MAC algorithm used for communication across the network boundary. The synchronous/asynchronous duty cycle MAC algorithm is practically evaluated by using a testbed. The experiment results suggest using the synchronous duty cycle protocol for communication across the network boundary consumes less energy offers improved latency and reliability than the previously proposed asynchronous duty cycle protocol.

Software Toolkit for Development of Interoperable Communications in Data-driven Systems

Abstract The ease of software development, maintenance, commissioning and reconfiguration is paramount in industrial systems, because these must be adaptable to changes in customer demand and the evolution of production assets. Such adaptations are a core motivator in the fourth industrial revolution. Additionally, software applications should be able to communicate over the logical and geographical borders of production plants, regardless of software platforms and vendors. However, these issues remains unaddressed in current software tools, although a solution is reachable with a proper software toolkit. As a solution, this article introduces such a toolkit to support the development of industrial software systems. The toolkit implements a communication stack with both a communication protocol and an information model. The long-term goal is to enable all communication in industrial plants with such a toolkit regardless of software products, vendors and platforms. Additionally, the toolkit provides auxiliary tools to help in the development of industrial software, such as services to provide historical data for simulation purposes. As an outcome, the toolkit provides insight about the development needs of industrial communications.

An Efficient RPL-Based Mechanism for Node-to-Node Communications in IoT

Routing discovery is a pivotal component of the communication stack in low-power and lossy networks (LLNs). The IPv6 routing protocol for LLNs, termed RPL, has been recently standardized to provide routing discovery in a wide range of LLN-based deployments realizing the Internet-of-Things (IoT) vision. RPL was mainly designed with the assumption that the predominant traffic flow would be gathering data toward a single destination, typically the root node. However, node-to-node (N2N) communication, where the root is neither a source nor destination, is a prime requirement in most of the LLN-based applications, such as actuating, decision making, and controlling applications. RPL in its current form does not cater well to such applications where there is a good number of inward N2N traffic flows. In this article, we propose a hybrid routing mechanism based on RPL for high N2N communications in LLNs referred to by HRPL. HRPL is implemented on Contiki and evaluated through extensive simulations on Cooja. HRPL is fully backward compatible with RPL where HRPL and RPL nodes can work together seamlessly in a hybrid network. Results show that HRPL provides a considerable improvement in the packet delivery ratio relative to the standardized RPL-based modes and to the RPL-based opportunistic routing approach. While HRPL requires a slightly larger memory footprint more than that for RPL, HRPL manages to significantly reduce the control plane packets, number of hops, and MAC transmissions needed to successfully deliver N2N data packets. Accordingly, this is translated to lower packet delay and less energy consumption.

A system design for elastically scaling transaction processing engines in virtualized servers

Online Transaction Processing (OLTP) deployments are migrating from on-premise to cloud settings in order to exploit the elasticity of cloud infrastructure which allows them to adapt to workload variations. However, cloud adaptation comes at the cost of redesigning the engine, which has led to the introduction of several, new, cloud-based transaction processing systems mainly focusing on: (i) the transaction coordination protocol, (ii) the data partitioning strategy, and, (iii) the resource isolation across multiple tenants. As a result, standalone OLTP engines cannot be easily deployed with an elastic setting in the cloud and they need to migrate to another, specialized deployment. In this paper, we focus on workload variations that can be addressed by modern multi-socket, multi-core servers and we present a system design for providing fine-grained elasticity to multi-tenant, scale-up OLTP deployments. We introduce novel components to the virtualization software stack that enable on-demand addition and removal of computing and memory resources. We provide a bi-directional, low-overhead communication stack between the virtual machine and the hypervisor, which allows the former to adapt to variations coming both from the workload and the resource availability. We show that our system achieves NUMA-aware, millisecond-level, stateful and fine-grained elasticity, while it is not intrusive to the design of state-of-the-art, in-memory OLTP engines. We evaluate our system through novel use cases demonstrating that scale-up elasticity increases resource utilization, while allowing tenants to pay for actual use of resources and not just their reservation.

Performance Analysis of Virtual Communication Between Thermal Cameras and Contact-tracing Applications for COVID-19

Late 2019 and a significant part of early 2020 have witnessed the outbreak of Coronavirus disease-19 (COVID-19) across the world. As a desperate attempt to control the virus spread, many countries are enforcing measures to restrict large concentration of people at one place and are implementing some form of contact tracing mobile application to quickly track close interactions between people. Furthermore, as businesses come out of lockdowns, they are required to record the temperature of all visitors and staffs that move in and out of their premises. Some businesses are employing medical grade contactless thermal imaging cameras for scanning temperature. Communication and sharing of information between the contact tracing application and thermal cameras would make an effective tool against COVID-19. However, there is a disconnect between the contact tracing applications and contactless thermal imaging solutions because they employ different communication stacks, platforms, data formats, and protocols. Furthermore, any kind of middleware to mediate between the cameras and the mobile applications would render the solution useless because of the induced latencies. In this paper, we are proposing to virtualize the communication between the cameras and mobile applications so that they could communicate and interoperate over a common protocol stack. We further model and simulate the proposed virtualized communication algorithm, under various topologies and configurations to comprehensively evaluate the performance, scalability, and deployment feasibility. The simulation aptly and efficiently evaluates the results for latency, energy, and bandwidth consumption parameters.

Implementation of a geographical routing scheme for low Earth orbiting satellite constellations using intersatellite links

SummaryA major problem for low Earth orbit (LEO) constellations with intersatellite links is the efficient routing of the data packets through such a highly dynamic network. In order to achieve a worldwide coverage even in remote areas and Internet access with a limited amount of gateway stations, intersatellite links are a promising approach. Since LEO constellations represent a distinct, highly dynamic routing environment, specific strategies are needed. To this end, a suitable geographical routing scheme is proposed and investigated in two Walker Star constellations. The proposed scheme targets reliable transmissions with low latency and high data rates. The approach is based on a geographical address identifier in Layer 2 of the communication stack. The globe is thus divided into geographical areas that determine this identifier in the MAC address of the terminals. As mobile terminals are considered, the MAC addressing scheme is flexible, whereas the IP addresses of the terminals remain static. This decoupling allows for flexibility in the choice of the address resolution scheme. Moreover, the geographical identifier in the MAC address enables fast routing table lookups and switching. The proposed routing scheme also takes possible overloads of the satellites due to traffic into account and applies a rerouting procedure. When a packet arrives in the geographical area of the destination terminal, a local rerouting scheme is applied if needed. The proposed approaches take handover events that possibly occur during a transmission into account. Furthermore, the scan angles of the satellites have been adapted to the constellations to provide full coverage and high elevation angles. So a robust and adaptable routing scheme is provided for a dynamic environment where satellites and terminals are constantly moving. The proposed definitions and procedures have been implemented in a system level simulator, which allows for comparisons with adjustable parameters in various scenarios. In this work, an Iridium‐like constellation and a megaconstellation are investigated and compared regarding the address resolution procedures, the average end‐to‐end transmission delay, and the dropping and rerouting rates. Additionally, the signaling overhead is compared with other approaches. The simulator and results of the simulations provide grounds for further research w.r.t. the routing in satellite constellations using intersatellite links.

Toward End-to-End, Full-Stack 6G Terahertz Networks

Recent evolutions in semiconductors have brought the terahertz band in the spotlight as an enabler for terabit-per-second communications in 6G networks. Most of the research so far, however, has focused on understanding the physics of terahertz devices, circuitry and propagation, and on studying physical layer solutions. However, integrating this technology in complex mobile networks requires a proper design of the full communication stack, to address link- and system-level challenges related to network setup, management, coordination, energy efficiency, and end-to-end connectivity. This paper provides an overview of the issues that need to be overcome to introduce the terahertz spectrum in mobile networks, from a MAC, network and transport layer perspective, with considerations on the performance of end-to-end data flows on terahertz connections.

Estimating End-to-End Latencies in Automotive Cyber-physical Systems

Controller networks in today's automotive systems consist of more than 100 ECUs connected by various bus protocols. Seamless operation of the entire system requires a well-orchestrated interaction of these ECUs. Consequently, to ensure safety and comfort, a performance analysis is an inherent part of the engineering process. Conducting such an analysis manually is expensive, slow, and error prone. Tool support is therefore crucial, and a number of approaches have been presented. However, most work is limited to either network latencies or software latencies which results in an analysis gap at the transition between different layers of the communication stack. The work presented here introduces an approach to close this gap. Furthermore, we discuss the integration of different methods to obtain an end-to-end latency analysis.

Performance Analysis of Constrained Device Virtualization Algorithm

Internet of Things aims to automate and add intelligence into existing processes by introducing constrained devices such as sensors and actuators. These constrained devices lack in computation and memory resources and are usually battery powered for ease of deployments. Due to their limited capabilities, the constrained devices usually host proprietary protocols, platforms, data formats and data structures for communications and therefore, are unable to communicate with devices from different vendors. This inability leads to interoperability issues in Internet of Things which, is in fact against the spirit of Internet of things which, envisions interconnection of billions of devices and hence, results in an isolated, vendor-locked and close-loop deployments of IoT solutions. Various approaches have been made by the industry and academia to resolve the interoperability issues amongst constrained devices. However, majority of the solutions are at different layers of the communication stack but do not provide a holistic solution for the problem. In more recent research, there have been theoretical proposals to virtualize constrained devices to abstract their data so that its always available to applications. We have adopted this technique in our research to virtualize the entire Internet of Things network so that virtual TCP/IP based protocols can operate on virtual networks for enabling interoperability. This paper proposes the operations of the Constrained Device Virtualization Algorithm and then simulates it in CloudSIM to derive performance results. The paper further highlights open issues for future research in this area.

The analysis of energy consumption in 6TiSCH network nodes working in sub-GHz band

The 6TiSCH communication stack enables IPv6 networking over the TSCH (Time Slotted Channel Hopping) mode of operation defined in IEEE 802.15.4. Lately, it becomes an attractive solution for Low power and Lossy Networks (LLNs), suitable for Industrial Internet of Things (IIoT) applications. This article introduces a credible energy consumption model for the 6TiSCH network nodes, operating in the 863-870 MHz band. It presents the analysis leading to the construction of the model as well as detailed verification through experimental measurements which showed 98% accuracy in determining power consumption for two different network topologies. The article includes reliable battery lifetime predictions for transit and leaf nodes along with other parametric study results.

Concurrent OFDM Demodulation and Turbo Decoding for Ultra Reliable Low Latency Communication

The Ultra-Reliable Low Latency Communication (URLLC) applications have been proposed in recent years, targeting a round-trip end-to-end latency less than 1 ms with high reliability. Therefore, an order of magnitude improvements are needed in all layers of the wireless communication stack. This is a particular challenge for the physical layer, where typically a processing time of the order of microseconds is required for the computationally intensive demodulation and error correction processing, among other operations. Conventionally, the reception of signals, the demodulation processing and the error correction processing are performed consecutively at the receiver. However, this approach is associated with processing times on the order of hundreds of microseconds, preventing URLLC. Therefore, this paper proposes a novel processing architecture, which is capable of performing reception, Orthogonal Frequency Division Multiplexing (OFDM) demodulation and turbo decoding concurrently, rather than consecutively, hence significantly reducing the processing time. In order to achieve concurrent operation, the OFDM demodulation is performed using a novel cumulative Fast Fourier Transform (FFT), which produces successively more reliable estimates of all transmitted symbols in each successive clock cycle. At the same time, a Fully-Parallel Turbo Decoder (FPTD) is used to recover successively more reliable estimates of all bits in each successive clock cycle.

The brain as a network cable: Transmission of a modulated optical signal between two computers via the human brain

Abstract The SSVEP response is used to transmit information in a unidirectional through-brain non-cognitive (entirely passive) communication channel. This, in effect, is connecting two otherwise disconnected computers through the brain, allowing us to consider the bandwidth of SSVEP encoding. The system uses green LEDs driven by a square wave to stimulate SSVEPs with EEG measurements being recorded by an EMOTIV EPOC. The stimulation and detection of SSVEPs is at the base of the channel - upon which a communication stack is implemented, allowing for character strings to be transmitted between an independent sender and receiver. The system was tested on four subjects, the best BER performance being achieved when using a PSDA detector on the O1 electrode with a 7,4 Hamming code being used as the FEC. A practical ITR of 25.6 bits/min was achieved. A prefix based transmission protocol was developed which allows the receiver to determine when a message is being sent and also allows the receiver to synchronise with the sender without the need for a secondary connection. The developed protocol correctly determined that a message was being sent across the channel 90% of the time with an average absolute synchronisation error of 0.397 s between sender and receiver.

Comparison of KVP and RSI for Controlling KUKA Robots Over ROS

In this work, an open-source ROS interface based on KUKAVARPROXY for control of KUKA robots is compared to the commercial closed-source Robot Sensor Interface available from KUKA. This comparison looks at the difference in how these two approaches communicate with the KUKA robot controller, the response time and tracking delay one can expect with the different interfaces, and the difference in use cases for the two interfaces. The investigations showed that the KR16 with KRC2 has a 50 ms response time, and RSI has a 120 ms tracking delay, with negligible delay caused by the ROS communication stack. The results highlight that the commercial inferface is more reliable for feedback control tasks, but the proposed interface gives read and write access to variables on the controller during execution, and can be used for simple motion and tooling control.

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

Carrier Aggregation in Satellite Communications: Impact and Performance Study

Carrier Aggregation (CA) is an integral part of current cellular networks. Its ability to enhance the peak data rate, to efficiently utilize the limited available spectrum resources and to satisfy the demand for data-hungry applications has drawn large attention from different wireless network communities. Given the benefits of CA in the terrestrial wireless environment, it is of great interest to analyze and evaluate the potential impact of CA in the satellite domain. In this article, we provide a brief introduction to the possible CA configurations, their deployment scenarios/use cases as well as their advantages, disadvantages, and challenges. Next, the problem of multiuser aggregation and access control design for CA in multi-beam high throughput satellite systems under practical system constraints is presented. In particular, we propose an efficient CA design solution that gives the optimal carrier-user assignment along with the percentage that each user exploits each carrier assuming that multiple users can be multiplexed in each carrier. Both inter-transponder and intra-transponder CA at the satellite payload level of the communication stack are considered. We propose a flexible carrier allocation approach for a CA-enabled multi-beam satellite system targeting a proportionally fair user demand satisfaction. Simulation results and analysis shed some light on this rather unexplored scenario and demonstrate the feasibility of the CA in satellite communication systems.